Mixed-Species Groups of Animals: Behavior, Community Structure, and Conservation presents a comprehensive discussion on the mixed-species groups of animals, a spectacular and accessible example of the complexity of species interactions. They are found in a wide range of animals, including invertebrates, fish, mammals and birds, and in different habitats, both terrestrial and aquatic, throughout the world. While there are more than 500 articles on this subject scattered in separate categories of journals, there has yet to be a general, cross-taxa book-length introduction to this subject that summarizes the behavior and community structure of these groups. The authors first survey the diversity of spatial associations among animals and then concentrate on moving groups. They review the major classes of theories that have been developed to explain their presence, particularly in how groups increase foraging efficiency and decrease predation. Finally, they explore the intricacies of species interactions, such as communication, that explain species roles in groups and discuss what implications these social systems have for conservation. Functions as a single resource for readers inside and outside of academia on mixed-species groups, serving as a foundation for future research in this field Begins with an empirical summary of mixed-species distribution and reviews how the theories explaining their adaptive benefits are supported by the evidence Includes many aspects of mixed-group behavior (e.g. foraging, communication, collective decision-making, dominance, social roles of species and leadership, relationship to conservation) that were not previously or easily accessible
This book discusses the evolution of the mechanisms by which prey avoid attack by their potential predators and questions how such defences are maintained through natural selection. Topics covered include camouflage, warning signals and mimicry.
Avoiding Attack discusses the diversity of mechanisms by which prey avoid predator attacks and explores how such defensive mechanisms have evolved through natural selection. It considers how potential prey avoid detection, how they make themselves unprofitable to attack, how they communicate this status, and how other species have exploited these signals. Using carefully selected examples of camouflage, mimicry, and warning signals drawn from a wide range of species and ecosystems, the authors summarise the latest research into these fascinating adaptations, developing mathematical models where appropriate and making recommendations for future study. This second edition has been extensively rewritten, particularly in the application of modern genetic research techniques which have transformed our recent understanding of adaptations in evolutionary genomics and phylogenetics. The book also employs a more integrated and systematic approach, ensuring that each chapter has a broader focus on the evolutionary and ecological consequences of anti-predator adaptation. The field has grown and developed considerably over the last decade with an explosion of new research literature, making this new edition timely.
Communication is an essential factor underpinning the interactions between species and the structure of their communities. Plant-animal interactions are particularly diverse due to the complex nature of their mutualistic and antagonistic relationships. However the evolution of communication and the underlying mechanisms responsible remain poorly understood. Plant-Animal Communication is a timely summary of the latest research and ideas on the ecological and evolutionary foundations of communication between plants and animals, including discussions of fundamental concepts such as deception, reliability, and camouflage. It introduces how the sensory world of animals shapes the various modes of communication employed, laying out the basics of vision, scent, acoustic, and gustatory communication. Subsequent chapters discuss how plants communicate in these sensory modes to attract animals to facilitate seed dispersal, pollination, and carnivory, and how they communicate to defend themselves against herbivores. Potential avenues for productive theoretical and empirical research are clearly identified, and suggestions for novel empirical approaches to the study of communication in general are outlined.
Shoals, swarms, flocks, herds--group formation is a widespread phenomenon in animal populations. It raises several interesting questions for behavioral ecologists. Why do animals form and live in groups, and what factors influence the ways in which they do this? What are the costs and benefits to an anmimal of group living? How are these influenced by ecological factors?
Written primarily for students embarking on an undergraduate bioscience degree, this primer provides an accessible, straightforward, and approachable guide to data presentation using R.
Circular Statistics in R provides the most comprehensive guide to the analysis of circular data in over a decade. Circular data arise in many scientific contexts whether it be angular directions such as: observed compass directions of departure of radio-collared migratory birds from a release point; bond angles measured in different molecules; wind directions at different times of year at a wind farm; direction of stress-fractures in concrete bridge supports; longitudes of earthquake epicentres or seasonal and daily activity patterns, for example: data on the times of day at which animals are caught in a camera trap, or in 911 calls in New York, or in internet traffic; variation throughout the year in measles incidence, global energy requirements, TV viewing figures or injuries to athletes. The natural way of representing such data graphically is as points located around the circumference of a circle, hence their name. Importantly, circular variables are periodic in nature and the origin, or zero point, such as the beginning of a new year, is defined arbitrarily rather than necessarily emerging naturally from the system. This book will be of value both to those new to circular data analysis as well as those more familiar with the field. For beginners, the authors start by considering the fundamental graphical and numerical summaries used to represent circular data before introducing distributions that might be used to model them. They go on to discuss basic forms of inference such as point and interval estimation, as well as formal significance tests for hypotheses that will often be of scientific interest. When discussing model fitting, the authors advocate reduced reliance on the classical von Mises distribution; showcasing distributions that are capable of modelling features such as asymmetry and varying levels of kurtosis that are often exhibited by circular data. The use of likelihood-based and computer-intensive approaches to inference and modelling are stressed throughout the book. The R programming language is used to implement the methodology, particularly its "circular" package. Also provided are over 150 new functions for techniques not already covered within R. This concise but authoritative guide is accessible to the diverse range of scientists who have circular data to analyse and want to do so as easily and as effectively as possible.
This book discusses the evolution of the mechanisms by which prey avoid attack by their potential predators and questions how such defences are maintained through natural selection. Topics covered include camouflage, warning signals and mimicry.
Written primarily for mid-to-upper level undergraduates, this compelling introduction to power analysis offers a clear, conceptual understanding of the factors that influence statistical power, as well as guidance on improving and presenting the outcomes of power analyses to justify experimental design decisions.
This book offers advice on the statistical analysis of small data sets (which are often used for ethical, financial, or practical reasons) for various designs and levels of measurement, helping researchers to analyse such data sets, but also to evaluate and interpret others' analyses.
Circular Statistics in R provides the most comprehensive guide to the analysis of circular data in over a decade. Circular data arise in many scientific contexts whether it be angular directions such as: observed compass directions of departure of radio-collared migratory birds from a release point; bond angles measured in different molecules; wind directions at different times of year at a wind farm; direction of stress-fractures in concrete bridge supports; longitudes of earthquake epicentres or seasonal and daily activity patterns, for example: data on the times of day at which animals are caught in a camera trap, or in 911 calls in New York, or in internet traffic; variation throughout the year in measles incidence, global energy requirements, TV viewing figures or injuries to athletes. The natural way of representing such data graphically is as points located around the circumference of a circle, hence their name. Importantly, circular variables are periodic in nature and the origin, or zero point, such as the beginning of a new year, is defined arbitrarily rather than necessarily emerging naturally from the system. This book will be of value both to those new to circular data analysis as well as those more familiar with the field. For beginners, the authors start by considering the fundamental graphical and numerical summaries used to represent circular data before introducing distributions that might be used to model them. They go on to discuss basic forms of inference such as point and interval estimation, as well as formal significance tests for hypotheses that will often be of scientific interest. When discussing model fitting, the authors advocate reduced reliance on the classical von Mises distribution; showcasing distributions that are capable of modelling features such as asymmetry and varying levels of kurtosis that are often exhibited by circular data. The use of likelihood-based and computer-intensive approaches to inference and modelling are stressed throughout the book. The R programming language is used to implement the methodology, particularly its "circular" package. Also provided are over 150 new functions for techniques not already covered within R. This concise but authoritative guide is accessible to the diverse range of scientists who have circular data to analyse and want to do so as easily and as effectively as possible.
Shoals, swarms, flocks, herds--group formation is a widespread phenomenon in animal populations. It raises several interesting questions for behavioral ecologists. Why do animals form and live in groups, and what factors influence the ways in which they do this? What are the costs and benefits to an animal of group living? How are these influenced by ecological factors? The authors familiarize the reader with cutting-edge ideas on the ecology and evolution of group-living animals, and detail fascinating case studies demonstrating them in action.
Avoiding Attack discusses the diversity of mechanisms by which prey avoid predator attacks and explores how such defensive mechanisms have evolved through natural selection. It considers how potential prey avoid detection, how they make themselves unprofitable to attack, how they communicate this status, and how other species have exploited these signals. Using carefully selected examples of camouflage, mimicry, and warning signals drawn from a wide range of species and ecosystems, the authors summarise the latest research into these fascinating adaptations, developing mathematical models where appropriate and making recommendations for future study. This second edition has been extensively rewritten, particularly in the application of modern genetic research techniques which have transformed our recent understanding of adaptations in evolutionary genomics and phylogenetics. The book also employs a more integrated and systematic approach, ensuring that each chapter has a broader focus on the evolutionary and ecological consequences of anti-predator adaptation. The field has grown and developed considerably over the last decade with an explosion of new research literature, making this new edition timely.
Communication is an essential factor underpinning the interactions between species and the structure of their communities. Plant-animal interactions are particularly diverse due to the complex nature of their mutualistic and antagonistic relationships. However the evolution of communication and the underlying mechanisms responsible remain poorly understood. Plant-Animal Communication is a timely summary of the latest research and ideas on the ecological and evolutionary foundations of communication between plants and animals, including discussions of fundamental concepts such as deception, reliability, and camouflage. It introduces how the sensory world of animals shapes the various modes of communication employed, laying out the basics of vision, scent, acoustic, and gustatory communication. Subsequent chapters discuss how plants communicate in these sensory modes to attract animals to facilitate seed dispersal, pollination, and carnivory, and how they communicate to defend themselves against herbivores. Potential avenues for productive theoretical and empirical research are clearly identified, and suggestions for novel empirical approaches to the study of communication in general are outlined.
Providing students with clear and practical advice on how best to organise experiments and collect data so as to make the subsequent analysis easier and their conclusions more robust, this text assumes no specialist knowledge.
Mixed-Species Groups of Animals: Behavior, Community Structure, and Conservation presents a comprehensive discussion on the mixed-species groups of animals, a spectacular and accessible example of the complexity of species interactions. They are found in a wide range of animals, including invertebrates, fish, mammals and birds, and in different habitats, both terrestrial and aquatic, throughout the world. While there are more than 500 articles on this subject scattered in separate categories of journals, there has yet to be a general, cross-taxa book-length introduction to this subject that summarizes the behavior and community structure of these groups. The authors first survey the diversity of spatial associations among animals and then concentrate on moving groups. They review the major classes of theories that have been developed to explain their presence, particularly in how groups increase foraging efficiency and decrease predation. Finally, they explore the intricacies of species interactions, such as communication, that explain species roles in groups and discuss what implications these social systems have for conservation. Functions as a single resource for readers inside and outside of academia on mixed-species groups, serving as a foundation for future research in this field Begins with an empirical summary of mixed-species distribution and reviews how the theories explaining their adaptive benefits are supported by the evidence Includes many aspects of mixed-group behavior (e.g. foraging, communication, collective decision-making, dominance, social roles of species and leadership, relationship to conservation) that were not previously or easily accessible
Written primarily for mid-to-upper level undergraduates, this compelling introduction to power analysis offers a clear, conceptual understanding of the factors that influence statistical power, as well as guidance on improving and presenting the outcomes of power analyses to justify experimental design decisions.
We live in the era of big data. However, small data sets are still common for ethical, financial, or practical reasons. Small sample sizes can cause researchers to seek out the most powerful methods to analyse their data, but they may also be wary that some methodologies and assumptions may not be appropriate when samples are small. The book offers advice on the statistical analysis of small data sets for various designs and levels of measurement, helping researchers to analyse such data sets, but also to evaluate and interpret others' analyses. The book discusses the potential challenges associated with a small sample, as well as the ways in which these challenges can be mitigated. General topics with strong relevance to small sample sizes such as meta-analysis, sequential and adaptive designs, and multiple testing are introduced. While the focus is on hypothesis tests and confidence intervals, Bayesian analyses are also covered. Code written in the statistical software R is presented to carry out the proposed methods, many of which are not limited to use on small data sets, and the book also discusses approaches to computing the power or the necessary sample size, respectively.
Written primarily for students embarking on an undergraduate bioscience degree, this primer provides an accessible, straightforward, and approachable guide to data presentation using R.
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